Undergraduate Course: Multilevel Modelling (SSPS10019)
Course Outline
| School | School of Social and Political Science |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
Credits | 20 |
| Home subject area | School (School of Social and Political Studies) |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | Multilevel models are becoming an increasingly popular method of analysis for situations where responses are grouped, such as in schools or other institutions, neighbourhoods, parliamentary constituencies, countries, or any other social or spatial clusters. A particular version of multilevel modelling is where there are multiple measures on each respondent, so that the grouping is of measures within person; where these multiple measures are taken on successive occasions, multilevel modelling provides a means of modelling individual change over time. This course will emphasise the practical application of multilevel models in social sciences. The main focus will be on multilevel models for continuous, binary and multinomial outcomes, with shorter introductory sessions on models for other outcomes. Analyses will be illustrated using MLwiN (a package for carrying out multilevel modelling available free to academics and university students) and lectures will be combined with practical sessions in order to reinforce concepts. |
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
| Additional Costs | None |
Information for Visiting Students
| Pre-requisites | None |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
Students will:
¿ understand the principles and assumptions underlying multilevel models for analysing quantitative, binary and multinomial outcomes;
¿ be able to estimate, confirm the validity of, and interpret such models using the MLwiN software;
¿ be able to use MLwiN to model individual change over time;
¿ be able to explain the results of multilevel models clearly to both specialist and non-specialist audiences.
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Assessment Information
40% mid-term exam (using multiple-choice questions). This will constitute a formative feedback event.
60% take home exam (students will conduct a series of analysis tasks and report them). |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Not entered |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not entered |
| Study Pattern |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | |
Course secretary | |
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